There are great expectations of Artificial Intelligence (AI) and Machine Learning (ML) technologies bringing a major breakthrough to Air Traffic Management (ATM), enabling a highly automated system able to deliver higher capacity. The reliability and safety of these systems, however, remains a key question for both users and operators and is a fundamental obstacle for the adoption of AI/ML technologies in any domain. The main objective of the EU-funded TAPAS project is to provide a set of principles and criteria which pave the way for the deployment of these technologies in ATM in a safe and trustworthy manner. eXplainable Artificial Intelligence (XAI) techniques, together with Visual Analytics, will help explore trade-offs between efficiency of AI implementations and the suitability for deployment in specific applications.
